Abstract
We propose a formalism for deriving parametrised ensembles of local neighbourhood operators on the basis of a complete family of scale-space kernels, which are apt for the measurement of a specific physical observable. The parameters are introduced in order to associate a continuum of a priori equivalent kernels with each scale-space kernel, each of which is tuned to a particular parameter value.
Ensemble averages, or other functional operations in parameter space, may provide robust information about the physical observable of interest. The approach gives a possible handle on incorporating multi-valuedness (transparancy) and visual coherence into a single model.
We consider the case of velocity tuning to illustrate the method. The emphasis, however, is on the formalism, which is more generally applicable.
This work was performed as part of the 3D Computer Vision Research Program, supported by the Dutch Ministry of Economic Affairs through a SPIN grant, and by the companies Agfa-Gevaert, Philips Medical Systems and KEMA. We thank J. Blom, M. van Eert, R. van Maarseveen and A. Salden for their stimulating discussions and software implementation.
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© 1992 Springer-Verlag Berlin Heidelberg
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Florack, L.M.J., ter Haar Romeny, B.M., Koenderink, J.J., Viergever, M.A. (1992). Families of tuned scale-space kernels. In: Sandini, G. (eds) Computer Vision — ECCV'92. ECCV 1992. Lecture Notes in Computer Science, vol 588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55426-2_2
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